Abstract

Exploration and exploitation of hydrocarbon reservoirs have been always time consuming with high risk and high cost. In this regard, assessment of reservoir characterizations and information about spatial distribution of its parameters play an important role in adaptation of suitable strategies for hydrocarbon resources management. There are only few numbers of oil wells cored in every oil field due to high cost, time-consuming process, and other drilling problems. Therefore, it is required to use alternative estimation methods in order to achieve the petro-physical parameter in total space of reservoir. In this research, geostatistical methods have been applied as a new approach to calculate and estimate porosity and permeability of reservoir in one of southwestern oil fields of Iran. The information obtained from 86 wells in one of southwestern oil fields of Iran has been available in this study. Physical parameters of porosity and permeability are vital parameters that should be estimated in studied reservoir. This study indicated that Gaussian Variogram Model is the best model to predict porosity and permeability values in field. Error means of actual values of porosity are equal to 6.9% and for permeability are 11.21% using Gaussian Model. Also, after prediction of porosity and permeability values for field, distribution of these parameters in field was illustrated in two-dimensional and three-dimensional modes besides distribution and location of wells in field in order to determine the best drilling spots and reduce risk of drilling operations.

Highlights

  • IntroductionHuman needs to recognize hydrocarbon reservoirs and their characterizations and features in order to reduce risk of exploration and exploitation of oil and gas resources

  • Physical parameters of porosity and permeability are critical parameters that should be estimated in studied reservoir

  • Regression coefficients and AARD% were equal to 0.97% and 6.3% for porosity and equal to 0.97% and 11.21% for permeability

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Summary

Introduction

Human needs to recognize hydrocarbon reservoirs and their characterizations and features in order to reduce risk of exploration and exploitation of oil and gas resources. In this regard, assessment of reservoir characterizations and information about spatial distribution of its parameters play an important role in adaptation of suitable strategies for hydrocarbon resources management [1]. Block three-dimensional estimation can be done for reservoir having a suitable network of wells, sampling and estimating well-stream parameters The advantage of this estimation is knowledge of spatial distribution of reservoir rock that plays a vital role in directing management strategies of oil reservoirs. According to the importance of petro-physical parameters through three-dimensional geostatistical well-stream estimation in oil reservoir rock, the general goals of this research are based on two major bases: 1) Identification and determination of mathematical-empirical regression model to estimate petro-physical parameters of oil reservoir in studied formation (Sarvak Formation)

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